Heating and cooling account for 50% of global energy consumption and 40% of energy related CO 2 emissions. Progress towards renewable heating has been slow, and Ireland is expected to miss European Union 2020 emission reduction and renewable energy targets. While increased wind penetration since 2005 has reduced the carbon intensity of Ireland's electricity by 29%, carbon intensity per used floor area is more than twice the European average, amplifying air pollution, climate change, and energy security issues. The heating and electricity sectors can benefit from the successful transition to cleaner, lower carbon electricity by electrifying heating. Electricity-driven heat pumps deliver 3-4 units of heat per unit of electricity consumed, thereby offering a 76% emission reduction compared with fossil-fuelled heating. This research offers an opportunity to minimise both running cost and emissions, assisting the end user and the environment. This is achieved using the smart grid to charge a thermal store during favourable lowcost times and discharge as required later. Smart, information and communication technology-integrated, adaptive control with artificial intelligence optimises the heat pump schedule based on information from forecasting services and/or predictions of heat demand, heat pump source quality, stored heat and day-ahead electricity prices. Another opportunity is the potential to assist the electricity grid by reducing peak electricity demand as smart control favours low electricity prices and low CO 2 intensity that coincide with the availability of cheap (wind) electricity. Demand is shifted from expensive peak demand periods, enabling the electrification of heating in a smart energy system.

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Grid-edge technologies (GET) enable and amplify the impact of three emerging energy system trends: electrification, decentralisation, and digitalisation. Smart grid integrated heat pumps with thermal energy storage enable both the electrification of heating and decentralised demand response. Such power-to-heat technologies simultaneously decarbonise heating and facilitate the grid integration of more variable renewable electricity in a cost-effective manner. This may help to explore and exploit untapped wind generation potential. This study explores the flexibility potential of a domestic scale heat pump with thermal energy storage in a typical Irish home in December. The system is simulated to investigate demand-side flexibility and sensitivity to both heat pump and thermal storage capacities for three days with wind energy shares of 7%, 25%, and 60%. Using real-time electricity prices and optimising for operational cost, the implicit demand flexibility potential is quantified with different combinations of heat pump power and storage capacity. The results suggest that 33-100% of critical loads can be shifted dynamically to low-cost periods. Optimised system design depends on local climate, heat demand profile, optimisation horizon, and the type of heat pump. Optimisation with genetic algorithm yielded near-global optimal results approximately 40 times faster than with exhaustive enumeration.